package com.atguigu.day06;

import com.atguigu.bean.WaterSensor;
import org.apache.flink.api.common.eventtime.*;
import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.api.java.tuple.Tuple;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.datastream.KeyedStream;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.datastream.WindowedStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.windowing.ProcessWindowFunction;
import org.apache.flink.streaming.api.windowing.assigners.TumblingEventTimeWindows;
import org.apache.flink.streaming.api.windowing.time.Time;
import org.apache.flink.streaming.api.windowing.windows.TimeWindow;
import org.apache.flink.util.Collector;

import java.time.Duration;

import static org.apache.flink.util.Preconditions.checkArgument;
import static org.apache.flink.util.Preconditions.checkNotNull;

public class Flink01_Flink_Custom_WaterMark {
    public static void main(String[] args) throws Exception {
        //1.获取流的执行环境
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(1);


        //TODO 设置WaterMark周期生成时间
//        env.getConfig().setAutoWatermarkInterval(1000);


        //2.从端口读取数据
        DataStreamSource<String> streamSource = env.socketTextStream("localhost", 9999);

        //3.将数据转为JavaBean，为了方便提取数据
        SingleOutputStreamOperator<WaterSensor> waterSensorDStream = streamSource.map(new MapFunction<String, WaterSensor>() {
            @Override
            public WaterSensor map(String value) throws Exception {
                String[] split = value.split(",");
                return new WaterSensor(split[0], Long.parseLong(split[1]), Integer.parseInt(split[2]));
            }
        });

        //TODO 4.指定WaterMark以及事件时间戳   使用有序流中的WaterMark
        SingleOutputStreamOperator<WaterSensor> waterSensorSingleOutputStreamOperator = waterSensorDStream.assignTimestampsAndWatermarks(new WatermarkStrategy<WaterSensor>() {
            @Override
            public WatermarkGenerator<WaterSensor> createWatermarkGenerator(WatermarkGeneratorSupplier.Context context) {
                return new MyWaterMarkGenerator(Duration.ofSeconds(3));
            }
        }
                //分配事件时间戳
                .withTimestampAssigner(new SerializableTimestampAssigner<WaterSensor>() {
                    @Override
                    public long extractTimestamp(WaterSensor element, long recordTimestamp) {
                        return element.getTs() * 1000;
                    }
                }));

        //5.将相同id的数据聚合到一块
        KeyedStream<WaterSensor, Tuple> keyedStream = waterSensorSingleOutputStreamOperator.keyBy("id");

        //TODO 6.开启一个基于事件时间的滚动窗口，窗口大小为5S
        WindowedStream<WaterSensor, Tuple, TimeWindow> window = keyedStream.window(TumblingEventTimeWindows.of(Time.seconds(5)));
        SingleOutputStreamOperator<String> process = window.process(new ProcessWindowFunction<WaterSensor, String, Tuple, TimeWindow>() {
            @Override
            public void process(Tuple tuple, ProcessWindowFunction<WaterSensor, String, Tuple, TimeWindow>.Context context, Iterable<WaterSensor> elements, Collector<String> out) throws Exception {
                String msg =
                        "窗口: [" + context.window().getStart() / 1000 + "," + context.window().getEnd() / 1000 + ") 一共有 "
                                + elements.spliterator().estimateSize() + "条数据 ";
                out.collect(msg);
            }
        });

        SingleOutputStreamOperator<WaterSensor> result = window.sum("vc");

        result.print();
        process.print();

        env.execute();


    }

    //TODO 自定义一个类实现WatermarkGenerator这个接口
    public static class MyWaterMarkGenerator implements WatermarkGenerator<WaterSensor>{

        //当前最大的时间戳
        private long maxTimestamp;

        //乱序程度（延迟时间）
        private long outOfOrdernessMillis;

        public MyWaterMarkGenerator(Duration maxOutOfOrderness) {
            //获取传入的乱序程度
            this.outOfOrdernessMillis = maxOutOfOrderness.toMillis();

            // 起始WaterMark的值为Long的最小值
            this.maxTimestamp = Long.MIN_VALUE + outOfOrdernessMillis + 1;
        }

        /**
         * 每来一条数据调用一次 可以生成WaterMark
         * @param event
         * @param eventTimestamp
         * @param output
         */
        @Override
        public void onEvent(WaterSensor event, long eventTimestamp, WatermarkOutput output) {
            maxTimestamp = Math.max(maxTimestamp, eventTimestamp);
            System.out.println("onEvent:生成WaterMark："+(maxTimestamp - outOfOrdernessMillis - 1));
//            output.emitWatermark(new Watermark(maxTimestamp - outOfOrdernessMillis - 1));
        }

        /**
         * 默认每隔200ms 调用一次 可以生成WaterMark
         * @param output
         */
        @Override
        public void onPeriodicEmit(WatermarkOutput output) {
            System.out.println("生成WaterMark："+(maxTimestamp - outOfOrdernessMillis - 1));
            output.emitWatermark(new Watermark(maxTimestamp - outOfOrdernessMillis - 1));
        }
    }
}
